In [12]:
import scipy.stats as stats
from statsmodels.stats.power import TTestPower
from matplotlib.patches import Patch
%config InlineBackend.figure_format = 'retina'
plt.rc('figure', dpi=300)
analysis = TTestPower()
fig = plt.figure(figsize=(30, 5*len(sample_sizes)),constrained_layout=True)
gs = fig.add_gridspec(len(sample_sizes), 5)
colors = {
'topological': matplotlib.colors.to_rgb('#027dad'),
'spatial': matplotlib.colors.to_rgb('#ad023b'),
}
logp_threshold = -np.log10(0.05)
for ci, task in enumerate(tasks):
for ri, sample_size in enumerate(sample_sizes):
ax = fig.add_subplot(gs[ri, ci])
sns.lineplot(
x=[0,1],
y=[0,1],
style=True,
color=(0,0,0),
legend=False,
linewidth=2,
dashes=[(2,2)],
ax=ax,
)
nauc = []
for method in ['spatial', 'topological',]:
tpr = [TPR[task][f'N={sample_size},CDT={cdt}'][method] for cdt in cdts]
fpr = [FPR[task][f'N={sample_size},CDT={cdt}'][method] for cdt in cdts]
ax.errorbar(
x=[i.mean(0) for i in fpr],
y=[i.mean(0) for i in tpr],
xerr=[1.96 * stats.sem(i, 0) for i in fpr],
yerr=[1.96 * stats.sem(i, 0) for i in tpr],
color=colors[method],
linewidth=3,
elinewidth=2,
capsize=3,
capthick=2,
)
nauc.append(
compute_normalized_partial_area_under_curve(
np.array([i.mean(0) for i in fpr]),
np.array([i.mean(0) for i in tpr]),
min([i.mean(0) for i in fpr]),
max([i.mean(0) for i in fpr]),
)
)
ax.set_ylim(-0.05,1.05)
leg = ax.legend(
handles=[Patch(facecolor=np.append(colors[m], 1),) for m in ['spatial', 'topological',]],
labels=['${:.1f}\%$'.format(100*x) for x in nauc],
loc='center right',
ncol=1,
fontsize=18,
title="$AUC$",
title_fontsize=24,
labelspacing=1.,
handlelength=1.,
)
leg.set_zorder(30)
for patch in leg.get_patches():
patch.set_width(20)
patch.set_height(20)
patch.set_y(-4)
xlabel = ''
if ri == len(sample_sizes) - 1:
xlabel = 'FPR'
ax.set_xlabel(xlabel, fontsize=40)
ax.set_xlim(-0.01,0.315)
ylabel = ''
if ci == 0:
ylabel = 'TPR'.format(task)
ax.set_ylabel(ylabel, fontsize=40)
ax.set_facecolor(np.array([234,234,242])/255)
ax.grid(color=(0.99,0.99,0.99,), linewidth=3)
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)
ax.tick_params(axis='both', colors=(0.5,0.5,0.5), labelcolor=(0,0,0), direction='out')
fig.legend(
handles=[Patch(facecolor=np.append(colors[m], 1),) for m in ['spatial', 'topological',]],
labels=['Spatial', 'TCS'],
loc='lower center',
bbox_to_anchor=(0.5, 1.0),
ncol=2, fontsize=40,
)
plt.show()
